1. Field of the Invention
This invention relates to signal transmission ranging systems, such as GPS, radar, sonar, lidar and the like, in which the generally deleterious multiple propagation path (multipath) induced ranging errors are operating. More specifically, this invention provides improvement in ranging error when secondary path signals are not far separated from the direct path signal.
2. Description of Related Art
The direct and each secondary path signal propagated to a signal receiver can be described by three parameters: amplitude, carrier phase, and signal modulation delay. Secondary path signals most generally result from reflections of direct path signals. Reflections are subject to additional propagation loss, delay, and electromagnetic effects (phase shift) characteristic of the reflecting materials. In toto, relative to the direct path signal, reflected signals are observed later in time with generally lower amplitude and with randomized phase. The difference in delay of secondary path signals and the direct path signal is here referred to as “path separation”—always a non-negative quantity. It is cognitively useful to normalize delay difference by multiplying by the speed of signal propagation to refer to path separation in distance (range) units.
It is understood in the art that ranging information is carried by both signal modulation and carrier phase. Carrier phase derived range is ambiguous from wavelength to wavelength. In short wavelength systems, modulation derived range is generally used to assist in resolving this ambiguity. Partly motivated by optimal methods for estimating range from noisy signal observations in systems with a priori information on signal modulation, range is obtained by correlating the received signal envelope with stored and delayed replicas of the signal modulation aligned with the received signal.
There are two methods in use for mitigating degradations in ranging accuracy caused by multiple signal propagation paths. The first, referred to here as the waveform method, uses specially designed waveforms as reference functions for cross-correlating with the received signal envelope. In GPS, as an example of a ranging system, range-to-satellite, referred to as pseudorange, can be measured by correlating the received signal envelope with two chipping sequences each the same as that broadcast by the GPS satellites but separated in time by some fraction of the duration of a chip. The difference in values between the correlation of the chipping sequences and the received signal is a discriminator function which, in a feedback loop referred to as a Delay Lock Loop (DLL), is delayed or advanced in time so that the chipping sequences straddle the received signal, producing a null at the delay or advance constituting the time of signal reception. The presence of multipath in the received signal causes the null to shift. This shift is a ranging error which may be very appreciable depending on the intensity of the multipath signal(s). In fact, multipath induced null shift when secondary path signals of appreciable intensity are observed is typically a dominant ranging error source.
The difference in correlation values between the received signal modulation and two chipping sequences separated by a given time increment can be obtained more directly by correlating the received signal envelope with the difference between these chipping sequences. The correlation of such bipolar functions with the received signal envelope varies from one polarity through a null to the other polarity which provides the DLL with the information needed to accomplish alignment with the received signal. For elaboration on this technique refer to Chapter 4-4 of the book entitled “Telecommunication Systems Engineering” by Lindsey, W. C. and Simon, M. K. published by Prentice-Hall, Inc. 1973 or the paper “Theory and Performance of Narrow Correlator Spacing in a GPS Receiver,” Van Dierendonck, et al in Proceedings of the National Technical Meeting, Institute of Navigation, 1992 pp. 115-124.
The bipolar pulses described above are in a sense the simplest of a class of correlator reference waveforms than have been devised to reduce the DLL null shift effect occurring when multipath is present. The reader is referred to U.S. Pat. No. 6,023,489 “Method and Apparatus for Code Synchronization in a Global Positioning System Receiver,” R. R. Hatch; and U.S. Pat. No. 6,272,189 “Signal Correlation Techniques for a Receiver of a Spread Spectrum Signal Including a Pseudorandom Noise Code that Reduces Errors when a Multipath Signal is Present,” L. Garin et al, for examples of these special waveforms. The somewhat more complex correlator reference waveforms described in these patents operate to provide improved multipath error performance at high path separation. Inherent in the behavior of a delay discriminator these special waveforms can have little to no effect on mitigating the null shift when the shift is small, perhaps less than several meters.
More optimal methods using classical Maximum Likelihood (ML) estimation techniques for mitigating the effects of multipath, in the sense that pseudorange errors are capable of being reduced to near unimprovable low levels when secondary path signals are observed, have been described in the patent records of the U.S. Patent office. This is emphasized by comparing the RMS delay estimate error with an ML estimator to an exemplary waveform delay estimator as displayed in FIG. 1. The reader is referred to U.S. Pat. No. 5,615,232 “Method of Estimating a Line of Sight Signal Propagation Time Using a Reduced Multipath Correlation Function,” R. D. J. Van Nee, and U.S. Pat. No. 6,370,207 “Method for Mitigating Multipath Effects in Radio Systems,” L. R. Weill, et al for elaboration on ML-based ranging methods. Prior to these inventions ML estimation in the case of multipath signals was infeasible for real-time processing applications. Van Nee forms the correlation of a reference chipping sequence with the received signal modulation. This function is reduced iteratively by estimating signal parameters using a search process for the next most intense secondary path signal remaining on each iteration and subtracting the correlation function estimated with those signal parameters. Weill, et al formulate the likelihood in terms of linearized functions related to the nuisance parameters of the direct and secondary path(s) signal(s) to reduce the ML estimation problem to a search in only the delay parameters of the direct and secondary path(s) signal components. As compared to a search over all the signal parameters, reduced search dimensionality is more rapidly executed by orders of magnitude, and is done in the interest of making feasible real-time ML quality range estimates.